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Research about New York

Source-linked reports with geographic coverage including New York.

At least 145 records · Page 8Linked to original sources
USGS2022

Using microbial source tracking to identify fecal contamination sources in Great South Bay on Long Island, New York

The U.S. Geological Survey worked in cooperation with the New York State Department of Environmental Conservation to assess the potential sources of fecal contamination entering a part of Great South Bay (referred to as Great South Bay for the purposes of this report) near the hamlets of West Sayville, Sayville, and Bayport on the southern shore of Suffolk County on Long Island, New York. Water samples are routinely collected by the New York State Department of Environmental Conservation in the bay and analyzed for fecal coliform bacteria, an indicator of fecal contamination, to determine the need for closure of shellfish beds for harvest and consumption. Fecal coliform and other bacteria are an indicator of the potential presence of pathogenic (disease-causing) bacteria. However, indicator bacteria alone cannot determine the biological or geographical sources of contamination; therefore, microbial source tracking was implemented to determine various biological sources of contamination. In addition, information such as the location, weather and season, and surrounding land use where a sample was collected help determine the geographical source and conveyance of land-based water to the embayment. Analysis revealed that the most substantial source of fecal contamination to Great South Bay was discharge from sites draining ponds and wetlands into the tributaries sampled, Brown and Green Creeks, particularly during the summer months. Fecal coliform bacteria at sites where ponds and wetlands drain are increased by stormwater runoff, which is another substantial source of fecal contamination. Sites with high concentrations of fecal coliform bacteria in the summer exacerbated by stormwater include the Brown Creek Culvert at Middle Road, Mill Pond Culvert near South Street, and Green Creek Culvert near Montauk Highway sites. The canine Bacteroides (BacCan) marker was the most frequently detected microbial source tracking marker with 15 positive detections in surface water across the landscape, followed by the waterfowl Helicobacter (GFD) marker with 9 detections and the human Bacteroides (HF183) marker with 4 detections in surface water (excluding 2 detections in sediment). The ruminant Bacteroides (Rum2Bac) marker was not detected in any samples collected during this study. The detection frequency of BacCan was similar for all sampling conditions and seasons, suggesting canine influence is unrelated to weather events and is a year-round occurrence. BacCan was detected in 14 of 16 source samples and only 1 of 16 receptor samples, which suggests that canine fecal contamination is likely diluted in the bay. There was a similar amount of marker detections when comparing weather condition (wet or dry) and season (winter or summer), suggesting that fecal contamination was unrelated to weather events or time of year. Eight waterfowl marker detections were in samples collected during the winter, and only one during the summer, implicating seasonal avian fecal contamination throughout the embayment. The human marker was detected in only one surface-water receptor sample, during the wet winter sampling event at the Green Creek Mid-Bay site. Three of four human marker detections were in the samples collected during the wet winter sampling event, indicating that weather and season may influence the presence of human markers in Great South Bay, but human markers are not overly prevalent.

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USGS2022

Application of a soil-water-balance model to estimate annual groundwater recharge for Long Island, New York, 1900–2019

A soil-water-balance (SWB) model was developed for Long Island, New York, to estimate the potential amount of annual groundwater recharge to the Long Island aquifer system from 1900 to 2019. The SWB model program is a computer code based on a modified Thornthwaite-Mather SWB approach and uses spatially and temporally distributed meteorological, land-cover, and soil properties as input to compute potential daily groundwater recharge. Simulated outputs indicate that island-wide potential groundwater recharge trends, as a percentage of precipitation, have increased approximately 3 percent during the 120-year period. The simulated results account for both climatic and land-cover changes that have occurred during the period. A change from undeveloped (forested land cover) to low- and medium-density residential land cover or land use increased potential groundwater recharge because of a decrease in evapotranspiration. During the 30-year period from 1900 to 1930, the simulated potential average groundwater recharge rate on Long Island was estimated to be 18.50 inches per year (in/yr), or a total of 1,243 million gallons per day, during the 30-year period from 1985 to 2015, the simulated potential average groundwater recharge rate estimate increased to 20.73 in/yr (a total of around 1,393 million gallons per day). During the 1900–2019 simulation period, the potential average annual groundwater recharge rate was about 19.24 in/yr. The data for that period included values for a 3-year meteorological drought from 1963 to 1965, where the mean precipitation was about 26.5 percent lower than the long-term average of 46.7 in/yr, and the potential groundwater recharge rate was about 12.3 in/yr. During a 3-year wet period from 1982 to 1984, where mean precipitation was about 19.6 percent higher than the long-term average, the estimated potential groundwater recharge rate was about 26.8 in/yr.

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USGS2022

Choosing an optimal duck season: Integrating hunter values and duck abundance

State wildlife agencies have long struggled to identify optimal hunting season dates for migratory game bird species that meet the diverse and often competing interests of stakeholders. Many approaches have been used to ensure the regulated community participates in the decision-making process, including public hearings, hunter season-date preference surveys, and hunter task forces or committees. Although hearings, surveys, and task force approaches include portions of the regulated community (typically the most avid) they may not necessarily reflect the opinions and values of all stakeholders. Additionally, these approaches rely heavily on limited anecdotal observations that may be unduly influenced by hunter avidity (e.g., days spent afield), hunter density, species preferences, and property access. To address the challenges caused by engaging only portions of the stakeholder community, we used a structured decision-making framework that included a 2017 duck hunter survey to elucidate values of a representative sample of the regulated community in each waterfowl hunting zone in the state of New York, USA. Rather than asking duck hunters about their specific duck hunting season date preferences, we asked them to rank 6 objectives describing what they value in their hunting experience (e.g., maximizing the opportunity to see mallards [ Anas platyrhynchos ] and black ducks [ Anas rubripes ], maximizing the number of weekend days). Four of the 6 objectives described duck species availability (i.e., abundance or immigration) and the remaining 2 described considerations that affect an individual hunter's opportunity or limitation to going duck hunting (i.e., holidays or conflicting hunting seasons). We used spatiotemporal abundance models derived from eBird citizen science data to estimate abundance and immigration rates of ducks in each waterfowl zone. We evaluated up to 9 unique season date alternatives developed by duck hunter task forces to determine which season date alternative best satisfied the competing objectives of duck hunters in each zone. The approach we developed allowed for selection of optimal duck hunting season dates and successfully involved avid duck hunters in the regulation development stages, while ensuring that the values of a representative sample of all stakeholders were directly considered through a clear and transparent decision-making process.

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USGS2022

Round Goby captured in a North American estuary: Status and implications in the Hudson River, New York

Round Goby Neogobius melanostomus , a nonnative fish species to North America, has been rapidly expanding through the connected waterways of the Laurentian Great Lakes. Herein, we document the eastward and southern expansion of Round Goby into the Hudson River, New York, an iconic coastal estuary that drains to Long Island Sound and the Atlantic seaboard. In summer and early fall 2021, routine fish monitoring conducted by the New York State Department of Environmental Conservation documented a population of Round Goby in the tidal portion of the Hudson River. Over the course of monitoring in 2021, personnel collected 112 Round Goby between Albany, New York, and Poughkeepsie, New York, with the southernmost collection occurring approximately 140 km downstream of invasion front as reported in 2020 within the New York State Canal System. Although Round Goby previously colonized large rivers and streams in the Great Lakes watershed, there is little information about the invasion success and ecological impacts of Round Goby in estuarine environments in North America. We discuss the distribution and biological characteristics of the Hudson River Round Goby population as well as the potential ecological implications and areas of future research and monitoring for this range expansion.

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USGS2022

Areas contributing recharge to selected production wells in unconfined and confined glacial valley-fill aquifers in Chenango River Basin, New York

In the Chenango River Basin of central New York, unconfined and confined glacial valley-fill aquifers are an important source of drinking-water supplies. The risk of contaminating water withdrawn by wells that tap these aquifers might be reduced if the areas contributing recharge to the wells are delineated and these areas protected from land uses that might affect the water quality. The U.S. Geological Survey, in cooperation with the New York State Department of Environmental Conservation and the New York State Department of Health, began an investigation in 2019 to improve understanding of groundwater flow and delineate areas contributing recharge to 16 production wells clustered in three study areas in the basin as part of an effort to protect the source of water to these wells. Areas contributing recharge were delineated on the basis of numerical steady-state groundwater-flow models representing long-term average hydrologic conditions. In the Cortland study area, four water suppliers operate 10 production wells that withdraw a total average rate of 2,480 gallons per minute from an unconfined aquifer consisting of well-sorted sand and gravel deposits. Simulated areas contributing recharge to these wells at their average pumping rates covered a total area of 6.93 square miles. Simulated areas contributing recharge extend upgradient from the wells to upland till deposits and to groundwater divides. Some simulated areas contributing recharge include isolated areas remote from the wells. Short simulated groundwater traveltimes from recharging locations to discharging wells indicated that the wells are vulnerable to contamination from land-surface activities; 50 percent of the traveltimes were 10 years or less. Land cover in some of the areas contributing recharge included a substantial amount of urban and agriculture land use. The groundwater-flow model of the Cortland study area was calibrated to available hydrologic data by inverse modeling using nonlinear regression. The parameter variance-covariance matrix from model calibration was used to create parameter sets that reflect the uncertainty of the parameter estimates and the correlation among parameters to evaluate the uncertainty associated with the single, predicted contributing areas to the wells. This analysis led to contributing areas expressed as a probability distribution. Because of the effects of parameter uncertainty, the size of the probabilistic contributing areas was larger than the size of the single, predicted contributing area for the wells. Thus, some areas not in the single, predicted contributing area might actually be in the contributing area, including additional areas of urban and agriculture land use that have the potential to contaminate groundwater. Additional areas that might be in the contributing area included recharge originating near the pumping wells that have relatively short groundwater-flow paths and traveltimes. In each of the Greene and Cincinnatus study areas, one water supplier operates three wells that are screened near the top of the bedrock surface in a confined aquifer consisting of poorly to well-sorted sand and gravel deposits. This confined aquifer is overlain by a lacustrine confining unit of very fine sand, silt, and clay, which in turn is overlain by a thin unconfined aquifer of sand and gravel. The groundwater-flow models for these two areas were manually calibrated because of the limited hydrologic data. Simulated areas contributing recharge to the Greene study area wells covered a total area of 0.35 square mile for the average pumping rate of 170 gallons per minute. The contributing areas extended southeastward of the wells to the groundwater divide in the till uplands. The contributing areas also included remote, isolated areas on the opposite side of the Chenango River from the wells primarily in the till uplands. For the Cincinnatus study area wells, which have a low average pumping rate (34 gallons per minute), the simulated contributing areas totaled 0.06 square mile and were on the same side of the river as the wells, but they are isolated areas remote from the wells primarily in the till-covered bedrock uplands. Land cover in these contributing areas for both study areas is primarily agriculture and forested, with the contributing areas to the Greene study area wells also including some urban land uses. Because the Greene and Cincinnatus study area wells are screened relatively deep and some flow paths to the wells partly travel through the confining unit, which impedes the connection with surface sources of recharge, overall groundwater traveltimes are greater than for wells in the Cortland study area. Fifty percent of Cortland study area wells, but only 9 and 44 percent of Greene and Cincinnatus study area wells, respectively, have groundwater traveltimes of 10 years or less.

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USGS2022

Areas contributing recharge to priority wells in valley-fill aquifers in the Neversink River and Rondout Creek drainage basins, New York

In southeastern New York, the villages of Ellenville, Wurtsboro, Woodridge, the hamlet of Mountain Dale, and surrounding communities in the Neversink River and Rondout Creek drainage basins rely on wells that pump groundwater from valley-fill glacial aquifers for public water supply. Glacial aquifers are vulnerable to contamination because they are highly permeable and have a shallow depth to water table. To protect the quality of these water resources, water managers need accurate information about the areas that contribute recharge to production wells that pump from these aquifers. The New York State Department of Environmental Conservation and the New York State Department of Health designated eight priority wells in this region for which water supply protection is of primary concern. The U.S. Geological Survey, in cooperation with the New York State Department of Environmental Conservation and the New York State Department of Health, began an investigation in 2019 with the general objectives of (1) improving understanding of regional groundwater-flow system, (2) delineating areas contributing recharge to eight priority production wells, and (3) quantifying the uncertainty of these contributing areas in a probabilistic way that can be used to inform decision-making related to priority well source-water protection. To complete these objectives, a MODFLOW 6 groundwater model was created encompassing the eight priority wells and the surrounding flow system, which includes parts of the Neversink River and Rondout Creek Basins in Sullivan County and Ulster County, New York. The model was built using Python tools (such as flopy , modflow-setup , and sfrmaker ) that facilitate transparent and repeatable model development using existing datasets. The model parameters were estimated with a stepwise approach using an iterative ensemble smoother implementation of the Parameter ESTimation software PEST++ (version 5.0.0). We evaluated initial “best guess” parameter bounds with a prior Monte Carlo analysis. Results of the first prior Monte Carlo analysis were used to make informed adjustments to model parameter bounds (typically resulting in expanded bounds), and a second prior Monte Carlo analysis was run to identify improved ranges for model parameters during history matching. The history matching effort produced an ensemble of parameter values for the groundwater-flow model that spans the range of values within prior uncertainty bounds. The ensemble is informed by the historical observation data, within a reasonable range of uncertainty on those observations. This history-matched ensemble was used in a particle tracking Monte Carlo analysis to delineate the areas contributing recharge to priority wells. The groundwater-flow and particle tracking (MODPATH7) models were run once for each ensemble member. Deterministic contributing areas computed for each ensemble member were aggregated to produce maps showing the probability that a location contributes recharge to priority wells. Finally, the particle tracking Monte Carlo analysis was repeated for six pumping scenarios, representing a wide range of possible pumping levels, to incorporate uncertainty in future pumping rates related to population growth or other management decisions. Increasing pumping rates generally led to larger contributing recharge areas and larger areas of high probability that a location contributes recharge to priority wells. These maps show the overall uncertainty of the areas contributing recharge to priority wells in the study area and provide a tool for risk-based decision making for protection of well source water.

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USGS2022

Data sources and methods for digital mapping of eight valley-fill aquifer systems in upstate New York

Digital hydrogeologic maps were developed in eight study areas in upstate New York by the U.S. Geological Survey in cooperation with the New York State Department of Environmental Conservation. The digital maps define the hydrogeologic framework of the valley-fill aquifers and surrounding till-covered uplands in the vicinity of the villages of Ellenville and Wurtsboro and hamlets of Woodbourne and South Fallsburg in Sullivan and Ulster Counties, town of Greene in Chenango County, city of Cortland and town of Cincinnatus in Cortland County, city of Jamestown in Chautauqua County, city of Olean and village of Ellicottville in Cattaraugus County, and villages of Fishkill and Wappinger Falls in Dutchess County. The hydrogeologic framework provided the foundation for groundwater-flow models that were used in the delineation of areas contributing groundwater flow to production wells screened in four of the eight valley-fill aquifers considered in this study. The hydrogeologic framework for the other four study areas was developed for potential future use in groundwater contributing-area studies. Data used in the creation of all digital surfaces and thicknesses included published surficial geology; aquifer maps and hydrogeologic sections; light detection and ranging (lidar) datasets; the Soil Survey Geographic Database; and lithologic well logs from the National Water Information System, New York State Department of Environmental Conservation, New York State Department of Transportation, and Empire State Organized Geologic Information System databases. Digital maps of the surficial geology; thickness of the surficial sand and gravel aquifers; and tops of the confining lacustrine silt and clay units, confined sand and gravel aquifers, and bedrock surfaces were created by using ArcGIS (a geographic information system). All surfaces and thicknesses were generated by using one of the following ArcGIS interpolation tools: Topo to Raster, Natural Neighbors, Kriging, or Empirical Bayesian Kriging. The datasets developed in this study provide a greater understanding of the underlying hydrogeologic framework in glacial valley-fill aquifers and can be applied in the evaluation of groundwater-supply development and protection.

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USGS2022

Using microbial source tracking to identify fecal contamination sources in Lake Montauk on Long Island, New York

The U.S. Geological Survey worked in cooperation with the Concerned Citizens of Montauk and the New York State Department of Environmental Conservation to assess the potential sources of fecal contamination entering Lake Montauk, an artificial embayment on the tip of the southern fork of Suffolk County, Long Island, New York. Water samples are routinely collected by the New York State Department of Environmental Conservation in the harbor and analyzed for fecal coliform bacteria, an indicator of fecal contamination, to determine the need for closure of shellfish beds for harvest and consumption. Fecal coliform and other bacteria are an indicator of the potential presence of pathogenic (disease-causing) bacteria. However, indicator bacteria alone cannot determine the biological or geographical sources of contamination; therefore, microbial source tracking was implemented to determine various biological sources of contamination. In addition, information such as the location, weather and season, and surrounding land use where a sample was collected help determine the geographical source and conveyance of land-based water to the embayment. Overall, human and waterfowl markers were infrequently and sporadically present in source and receptor samples at low concentrations. By evaluating the microbial source tracking markers alongside fecal coliform data and land-use information, geographical sources of fecal contamination discharging from various source sites, such as culverts and ponds, were better differentiated. Analysis revealed that stormwater runoff and pond drainage were the most likely transport mechanisms for fecal contamination to Lake Montauk. When considering Lake Montauk as a whole, the highest frequency of fecal coliform detections in source site samples was found to be under wet summer conditions, as evidenced by the high fecal coliform concentrations at the South Beach, Stepping Stones Pond, and Stepping Stones Pond Culvert sites (300, 220, and more than 16,000 most probable number per 100 milliliters, respectively). No point sources of fecal coliform contamination to Lake Montauk were identified; however, receptor site samples adjacent to marinas (Lake Montauk Inlet and Star Island North sites) had a high frequency of human marker detections but were associated with fecal coliform concentrations at or below the reporting limit. The absence of fecal coliform and human microbial source tracking markers in groundwater samples indicated that water from septic systems did not influence the lake during this study. Further, the sandy sediment sample collected at the South Beach site was negative for all microbial source tracking markers and is unlikely to contribute fecal coliform from the tested host organisms when resuspended in the water column through tidal shifts or boat activity.

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USGS2022

Predicted sea-level rise-driven biogeomorphological changes on Fire Island, New York: Implications for people and plovers

Forecasting biogeomorphological conditions for barrier islands is critical for informing sea-level rise (SLR) planning, including management of coastal development and ecosystems. We combined five probabilistic models to predict SLR-driven changes and their implications on Fire Island, New York, by 2050. We predicted barrier island biogeomorphological conditions, dynamic landcover response, piping plover ( Charadrius melodus ) habitat availability, and probability of storm overwash under three scenarios of shoreline change (SLC) and compared results to observed 2014/2015 conditions. Scenarios assumed increasing rates of mean SLC from 0 to 4.71 m erosion per year. We observed uncertainty in several morphological predictions (e.g., beach width, dune height), suggesting decreasing confidence that Fire Island will evolve in response to SLR as it has in the past. Where most likely conditions could be determined, models predicted that Fire Island would become flatter, narrower, and more overwash-prone with increasing rates of SLC. Beach ecosystems were predicted to respond dynamically to SLR and migrate with the shoreline, while marshes lost the most area of any landcover type compared to 2014/2015 conditions. Such morphological changes may lead to increased flooding or breaching with coastal storms. However—although modest declines in piping plover habitat were observed with SLC—the dynamic response of beaches, flatter topography, and increased likelihood of overwash suggest storms could promote suitable conditions for nesting piping plovers above what our geomorphology models predict. Therefore, Fire Island may offer a conservation opportunity for coastal species that rely on early successional beach environments if natural overwash processes are encouraged.

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USGS2022

Using microbial source tracking to identify fecal contamination sources in Sag Harbor on Long Island, New York

The U.S. Geological Survey worked in cooperation with the New York State Department of Environmental Conservation to assess the potential sources of fecal contamination entering Sag Harbor, an embayment complex on the northern shore of the south fork of Suffolk County, Long Island, New York. Water samples are routinely collected by the New York State Department of Environmental Conservation in the harbor and analyzed for fecal coliform bacteria, an indicator of fecal contamination, to determine the need for closure of shellfish beds for harvest and consumption. Fecal coliform and other bacteria are an indicator of the potential presence of pathogenic (disease-causing) bacteria. However, indicator bacteria alone cannot determine the biological or geographical sources of contamination; therefore, microbial source tracking was implemented to determine various biological sources of contamination. In addition, information such as the location, weather and season, and surrounding land use where a sample was collected help determine the geographical source and conveyance of land-based water to the embayment. Analysis revealed that the most substantial source of fecal contamination to Sag Harbor was discharge from sites draining ponds and wetlands, particularly during the summer months. Fecal coliform bacteria at sites where ponds and wetlands drain are increased by stormwater runoff, which is another substantial source of fecal contamination. Human markers were detected in all four samples at the Sag Harbor Sewage Treatment Plant Outfall site but were associated with low fecal coliform concentrations, indicating that the sewage treatment plant is not a likely source of fecal contamination to the embayment. The Ligonee Brook Culvert, Paynes Creek near Marjorie Lane, and Otter Pond Culvert sites were identified as locations that contribute fecal contamination to Sag Harbor. These three locations had high fecal coliform bacteria concentrations in the summer, one of which was positive for canine microbial source tracking markers (Ligonee Brook Culvert), and another positive for waterfowl markers (Paynes Creek near Marjorie Lane). The absence of fecal coliform bacteria and human microbial source tracking markers in groundwater samples indicates that water from septic systems does not influence the harbor; however, elevated fecal coliform bacteria concentrations were not often detected. Further, the sandy sediment alongside Sag Harbor is unlikely to contribute fecal coliform bacteria when resuspended in the water column through tidal shifts or boat activity.

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USGS2022

Bed-material transport in the upper Esopus Creek watershed, Ulster and Greene Counties, New York, 2017–20

The U.S. Geological Survey, in cooperation with the Ashokan Watershed Stream Management Program, investigated the feasibility of bedload monitoring in the upper Esopus Creek watershed, Ulster and Greene Counties, New York, from 2017 to 2020. Traditional bedload samples were collected at two locations: Birch Creek at Big Indian, New York (station 013621955), and Stony Clove Creek at Jansen Road at Lanesville, New York (station 01362336), during two storms. Measured bedload-transport rates ranged from less than 1 to 37.2 short tons per day during the study period. Active and passive tracers were deployed in Stony Clove Creek at Jansen Road to measure bed-material displacement during storms. Accelerometers in the active tracers provided data on the initiation and duration of motion of bed material in the 128- to 190-millimeter size class (B-axis measurement of 175 millimeters). The active tracers were loosely placed on the streambed and were generally mobilized at streamflows of 130–375 cubic feet per second. Displacement of the passive tracers was measured five times and provided data on the variability of displacement of multiple-size classes of bed material by different streamflows. Passive-tracer data also indicated that particles larger than the opening of the Elwha sampler deployed for traditional sampling may have been in transport during sampling. Sediment-generated noise was not distinguishable from background stream noise in hydrophone recordings.

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USGS2022

Using microbial source tracking to identify fecal contamination sources in Patchogue and Bellport Bays on Long Island, New York

The U.S. Geological Survey worked in cooperation with the New York State Department of Environmental Conservation to assess the potential sources of fecal contamination entering Patchogue and Bellport Bays, two embayments on the south shore of Suffolk County, Long Island, New York. Water samples are routinely collected by the New York State Department of Environmental Conservation in the bays and analyzed for fecal coliform bacteria, an indicator of fecal contamination, to determine the need for closure of shellfish beds for harvest and consumption. Fecal coliform and other bacteria are an indicator of the potential presence of pathogenic (disease-causing) bacteria. However, indicator bacteria alone cannot determine the biological or geographical sources of contamination; therefore, microbial source tracking was implemented to determine various biological sources of contamination. In addition, information such as the location, weather and season, and surrounding land use where a sample was collected help determine the geographical source and conveyance of land-based water to the embayment. Analysis revealed that the most substantial source of fecal contamination to Patchogue and Bellport Bays was discharge from sites draining ponds and wetlands into the rivers and tributaries sampled, particularly during the summer months. Fecal coliform bacteria at sites where ponds and wetlands drain are increased by stormwater runoff, which is another substantial source of fecal contamination. Overall, canine- and waterfowl-associated bacterial contributions were prevalent in source samples in both bays. Human-associated markers were present in surface-water source samples and completely absent in receptor samples in Patchogue Bay. The Fireplace Neck receptor site in Bellport Bay had a human-associated marker present in the summer wet sample only. Human markers were detected at the sample site downstream from the Patchogue wastewater treatment plant but were associated with low fecal coliform concentrations, indicating that the wastewater treatment plant is not a likely source of fecal contamination to Patchogue Bay. The lack of human-associated marker detections within Patchogue and Bellport Bays in summer source samples coupled with low to no detections of fecal coliform, especially where small marinas are present in creeks and tributaries, suggest that boats do not substantially contribute fecal coliform bacteria to the bays. There was little evidence of groundwater-contributing fecal bacteria by direct discharge from the subsurface. Further, the sandy sediment alongside Patchogue and Bellport Bays is unlikely to contribute fecal coliform bacteria from the test host organisms when resuspended in the water column. A classification scheme was developed to convey the degree of fecal contamination to stakeholders and resource managers. Based on this classification scheme, the Corey Creek Near Middle Road, Patchogue River Near Division Street, and Swan River Mouth sampling sites were identified as locations that contribute substantial fecal contamination to Patchogue Bay. In Bellport Bay, the Culvert at Beaverdam Creek site was identified as the location contributing the most substantial fecal contamination.

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USGS2022

Using microbial source tracking to identify contamination sources in Port Jefferson Harbor, Setauket Harbor, and Conscience Bay on Long Island, New York

The U.S. Geological Survey worked in cooperation with the New York State Department of Environmental Conservation to assess the potential sources of fecal contamination entering Port Jefferson Harbor, Setauket Harbor, and Conscience Bay, an embayment complex on the northern shore of Suffolk County, Long Island, New York. Water samples are routinely collected by the New York State Department of Environmental Conservation in the harbor and analyzed for fecal coliform bacteria, an indicator of fecal contamination, to determine the need for closure of shellfish beds for harvest and consumption. Fecal coliform and other bacteria are an indicator of the potential presence of pathogenic (disease-causing) bacteria. However, indicator bacteria alone cannot determine the biological or geographical sources of contamination; therefore, microbial source tracking was implemented to determine various biological sources of contamination. In addition, information such as the location, weather and season, and surrounding land use where a sample was collected help determine the geographical source and conveyance of land-based water to the embayment. Our analysis revealed that the most substantial source of fecal contamination to the Port Jefferson Harbor complex was discharge from sites draining ponds and wetlands, particularly during the summer months. Fecal coliform bacteria at sites where ponds and wetlands drain are increased by stormwater runoff, which is another substantial source of fecal contamination. Human markers, likely originating from the outfall of the Port Jefferson sewage treatment plant, were found at least once in every sample collected within Port Jefferson Harbor; however, fecal coliform concentrations were low, indicating that the sewage treatment plant is not a likely source of fecal contamination to the embayment. Canine markers detected in Conscience Bay were associated with high fecal coliform, particularly in wet summer samples. Waterfowl markers were most often detected in source water for Port Jefferson Harbor, but in Conscience Bay, waterfowl was frequently detected within the bay itself. Resuspension of bed sediment may contribute to fecal contamination in the harbor, but more targeted analyses are needed to support this finding. There was little evidence of groundwater-contributing fecal bacteria by direct discharge from the subsurface. A classification scheme was developed to convey the degree of fecal contamination to stakeholders and resource managers. Based on this classification scheme, the Culvert North of State Route 25A, Culvert North of Shore Road, Old Mill Creek Culvert, and Mill Pond Culvert to Conscience Bay sites were identified as locations that contribute substantial fecal contamination to the Port Jefferson Harbor complex.

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USGS2022

Hydrogeology of aquifers within the Fairport-Lyons channel system and adjacent areas in Wayne, Ontario, and Seneca Counties, New York

A hydrogeologic investigation was undertaken by the U.S. Geological Survey, in cooperation with the New York State Department of Environmental Conservation, within the areas shown in the Macedon, Palmyra, Newark, and Lyons 7.5-minute quadrangle maps that include parts of Wayne, Ontario, and Seneca Counties in New York. The most productive zone of aquifers within the study area is associated with the Fairport-Lyons glacial-stream channel (hereinafter referred to as the “Fairport-Lyons channel”) in southern Wayne County and adjacent areas. The Fairport-Lyons channel is a west-east-oriented bedrock channel that once served as the outlet for glacial Lake Dawson, which occupied the Genesee Valley near Rochester during the Pleistocene. The Fairport-Lyons channel and intersecting subsidiary channels are hereinafter referred to as the “Fairport-Lyons channel system.” Glacial meltwater eroded this shallow channel network into the underlying bedrock, and the channels subsequently filled with interlayered glaciofluvial sand and gravel and fine-grained lacustrine deposits. These sand and gravel deposits provide the only large supplies of groundwater in Wayne County under unconfined and confined conditions and serve a population of over 20,000 through a combination of domestic and municipal water supply wells. The largest reported well yield, 1,200 gallons per minute, is from an industrial supply well near Newark, N.Y. Much of the sand and gravel within the Fairport-Lyons channel system is generally thinly saturated; however, in three areas—near Macedon, Newark, and Lyons, N.Y.—the saturated thickness of the aquifer is sufficient to support groundwater yields adequate for municipal and industrial use, in part because of induced infiltration from the Erie Canal.

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USGS2022

A machine learning approach to identify barriers in stream networks demonstrates high prevalence of unmapped riverine dams

Restoring stream ecosystem integrity by removing unused or derelict dams has become a priority for watershed conservation globally. However, efforts to restore connectivity are constrained by the availability of accurate dam inventories which often overlook smaller unmapped riverine dams. Here we develop and test a machine learning approach to identify unmapped dams using a combination of publicly available topographic and geospatial habitat data. Specifically, we trained a random forest classification algorithm to identify unmapped dams using digitally engineered predictor variables and known dam sites for validation. We applied our algorithm to two subbasins in the Hudson River watershed, USA , and quantified connectivity impacts, as well as evaluated a range of predictor sets to examine tradeoffs between classification accuracy and model parameterization effort. The random forest classifier achieved high accuracy in predicting dam sites (true positive rate = 89%, false positive rate = 1.2%) using a subset of variables related to stream slope and presence of upstream lentic habitats. Unmapped dams were prevalent throughout the two test watersheds. In fact, existing dam inventories underestimated the true number of dams by ∼80–94%. Accounting for previously unmapped dams resulted in a 62–90% decrease in dendritic connectivity indices for migratory fishes. Unmapped dams may be pervasive and can dramatically bias stream connectivity information. However, we find that machine learning approaches can provide an accurate and scalable means of identifying unmapped dams that can guide efforts to develop accurate dam inventories, thereby informing and empowering efforts to better manage them.

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USGS2022

Condition of resident fish communities in the Eighteenmile Creek Area of Concern, New York

The lower 3.5 km of Eighteenmile Creek, a tributary to Lake Ontario in New York, was designated as an Area of Concern (AOC) in 1985 under the Great Lakes Water Quality Agreement due to extensive contamination of bed sediments by polychlorinated biphenyls (PCBs) and other toxicants. Five beneficial use impairments (BUIs) have been identified in this AOC, including degraded fish and wildlife populations. We surveyed fish communities in the Eighteenmile Creek AOC and in a comparable section of a nearby reference stream (Oak Orchard Creek) during June 2019 to infer whether legacy contaminants are currently impairing fish communities in the AOC to an extent that they differ from the regional reference condition. Estimates of community abundance, biomass, diversity, and fish condition from each system were compared using a noninferiority testing framework. Biomass, diversity, and fish condition in the Eighteenmile Creek AOC were similar or superior to that in Oak Orchard Creek, while abundance was 20% lower in the AOC. These findings and those of a 2007 sampling effort suggest that fish communities in the Eighteenmile Creek AOC are not impaired despite recent studies indicating that PCBs are bioaccumulating in fish tissues at 1–2 orders of magnitude above background levels. Future assessments in the Eighteenmile Creek AOC might focus on the condition of benthic macroinvertebrate communities and potential toxicity of local contaminants to piscivorous wildlife in order to fully address the remaining aspects of the fish and wildlife populations beneficial use impairment.

New York↗
USGS2022

Depth drives growth dynamics of dreissenid mussels in Lake Ontario

Understanding dreissenid mussel population dynamics and their impacts on lake ecosystems requires quantifying individual growth across a range of habitats. Most dreissenid mussel growth rates have been estimated in nutrient rich or nearshore environments, but mussels have continued to expand into deep, cold, low-nutrient habitats of the Great Lakes. We measured annual quagga mussel ( Dreissena rostriformis bugensis) growth at 15 m, 45 m, and 90 m in Lake Ontario using caged mussels near Oswego, New York, USA from June 2018 to May 2019. Quagga mussel growth (starting size 12 mm) was greatest at 15 m (mean shell length increase = 10.2 mm), and was lower at 45 m (5.9 mm) and 90 m (0.7 mm). Caged mussels were obtained from near the 90-m site and those reared at 15 and 45 m developed thicker shells than those that were caged at 90 m. We observed relatively high colonization by quagga and, to a lesser degree, zebra mussels ( Dreissena polymorpha ) at 15 m, very few colonizers at 45 m, and none at 90 m. Higher growth potential, but low natural mussel densities observed at 15 m and 45 m suggest factors other than growth limit dreissenid abundance at these depths. The relatively slow dreissenid growth rates observed in offshore habitats are consistent with the gradual abundance increases documented in these zones across the Great Lakes and suggest new mussels that become established in these habitats may contribute to ecosystem effects for decades.

New York↗
USGS2022

Condition of macroinvertebrate communities in the Buffalo River Area of Concern following sediment remediation

The lower 10 km of the Buffalo River, a tributary to Lake Erie, was designated as an Area of Concern (AOC) in 1987 through the Great Lakes Water Quality Agreement because sediment contamination and habitat alteration from past industrialization caused several Beneficial Use Impairments (BUIs). Extensive remediation efforts conducted between 2011 and 2015 removed approximately 688,100 cubic meters of contaminated sediment from the Buffalo River AOC, and subsequent chemical analysis of sediments indicated that most remedial goals had been achieved. Benthic macroinvertebrate communities and sediment toxicity were evaluated in the AOC and an upstream reference area in 2017 and 2020 to determine whether remediation has improved benthic conditions sufficiently that the benthos BUI designation can be removed. Community condition was characterized using the New York State multi-metric index of biological integrity and bed sediments were used for 10-day toxicity tests with Chironomus dilutus and Hyalella azteca . Macroinvertebrate communities were classified as moderately to slightly impacted at most AOC sites compared to slightly impacted at most reference sites, but toxicity tests did not identify any evidence of toxicity in sediments from the AOC. A linear mixed effects model indicated that total organic carbon concentration in sediments, distance upstream from the river mouth, and the relative dominance of zebra mussels Dreissena polymorpha were the primary predictors of macroinvertebrate community condition. These findings are consistent with those from other AOCs in New York which indicate that contemporary benthic communities are generally shaped by legacy habitat alterations rather than AOC-specific sediment contamination and toxicity.

New York↗